scholarly journals Design and Control of a Multi-Functional Energy Recovery Power Accumulator Battery Pack Testing System for Electric Vehicles

Energies ◽  
2014 ◽  
Vol 7 (3) ◽  
pp. 1376-1392 ◽  
Author(s):  
Bo Long ◽  
Ji Ryu ◽  
Shin Lim ◽  
Kil Chong
Keyword(s):  
Electric Vehicles ◽  
Energy Recovery ◽  
Battery Pack ◽  
Testing System ◽  
Accumulator Battery ◽  
And Control

Trip Specific Worthiness of Replacement of Individual Cells for Battery Pack in Electric Vehicles

2011 ◽  
Author(s):  
Rohit Ugle ◽  
Yaoyu Li
Keyword(s):  
Real Time ◽  
Electric Vehicles ◽  
Battery Pack ◽  
Performance Gain ◽  
Intrinsic Signals ◽  
Battery Packs ◽  
On Line ◽  
The Individual ◽  
And Control ◽  
Battery Module

Ever increasing acceptance of electric vehicles relies on better operation and control of large battery packs. The individual cells in the large battery packs cannot have identical characteristics and may degrade differently due to its manufacturing variability and other factors. It is beneficial to evaluate the performance gain by replacing certain battery modules/cells during actual driving. We have a two-fold objective for this research. First, we are developing an on-line battery module degradation diagnostic scheme using the intrinsic signals of a battery pack equalization circuit. Therefore, a battery “health map” can be constructed and updated in real time. Secondly, based on the derived battery health map, the performance of the battery pack will be evaluated for customer specified trip so as to evaluate the “worthiness of replacing” certain modules/cells.

scholarly journals Task Planner for Robotic Disassembly of Electric Vehicle Battery Pack

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 387
Author(s):  
Martin Choux ◽  
Eduard Marti Bigorra ◽  
Ilya Tyapin
Keyword(s):  
Computer Vision ◽  
Electric Vehicles ◽  
Measurement Errors ◽  
Vision System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Computer Vision System ◽  
Electric Vehicle Battery ◽  
Robotic Disassembly ◽  
Total Average

The rapidly growing deployment of Electric Vehicles (EV) put strong demands on the development of Lithium-Ion Batteries (LIBs) but also into its dismantling process, a necessary step for circular economy. The aim of this study is therefore to develop an autonomous task planner for the dismantling of EV Lithium-Ion Battery pack to a module level through the design and implementation of a computer vision system. This research contributes to moving closer towards fully automated EV battery robotic dismantling, an inevitable step for a sustainable world transition to an electric economy. For the proposed task planner the main functions consist in identifying LIB components and their locations, in creating a feasible dismantling plan, and lastly in moving the robot to the detected dismantling positions. Results show that the proposed method has measurement errors lower than 5 mm. In addition, the system is able to perform all the steps in the order and with a total average time of 34 s. The computer vision, robotics and battery disassembly have been successfully unified, resulting in a designed and tested task planner well suited for product with large variations and uncertainties.

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